AI news archive.
19,856 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSafin-1.5: Safety-Native Architecture and Verifiable Reasoning for Recursive Safety Improvement
arXiv:2610.40751v1 Announce Type: cross Abstract: Recursive self-improvement (RSI) enables large language models to advance their capabilities through successive updates, but these updates can also introduce new risks an…
- arXiv cs.AIagents"Shall We Approve?" Consequence-Aware Approval for Autonomous Coding Agents
arXiv:2610.40753v1 Announce Type: cross Abstract: Coding agents increasingly rely on automated approvers to decide whether a proposed shell command may run. Existing approvers, from rule-based checkers to guardrail model…
- arXiv cs.AIresearchAutoHebb: Self-Modifying Neural Networks that Zero-Shot Infer and Continually Learn
arXiv:2610.40757v1 Announce Type: cross Abstract: Humans and animals have a unique capacity to generalize and learn in novel circumstances, including "0-shot" inference (ZI) and continual learning (CL) -- two powerful co…
- arXiv cs.AIresearchTAPE: Learning General Audio Effect Representations
arXiv:2610.40759v1 Announce Type: cross Abstract: Musicians and mixing engineers often can decipher the signal processing chain they hear on a reference recording, then adapt it to new material. We present TAPE (Transfor…
- arXiv cs.AIresearchFrom Teleoperation to Long-Horizon Dexterity: Evaluating Visuomotor Skills and Offline Proxies for Dexterous Manipulation
arXiv:2610.40828v1 Announce Type: cross Abstract: Imitation learning policies are intended to make robotic manipulation robust to variations in object pose, appearance, and environment that challenge pre-programmed motio…
- arXiv cs.AIresearchThe Generative Gap Between Speculative Drafter and Continuous Diffusion Language Model
arXiv:2610.40847v1 Announce Type: cross Abstract: Continuous diffusion language models (CDLMs) and speculative drafters offer efficient language generation but are typically evaluated differently: CDLMs generate independ…
- arXiv cs.AIresearchGraphTFactor: A graph-based approach for proteins transcription factor prediction
arXiv:2610.40867v1 Announce Type: cross Abstract: Transcription factors (TFs) play an important role in regulating gene expression, making their identification a fundamental task in computational biology. In this work, w…
- arXiv cs.AIagentsTSFLab: A Self-Improving Agent-Agnostic Workbench for Time Series Forecasting Research
arXiv:2610.40901v1 Announce Type: cross Abstract: As publications and products on time series forecasting (TSF) proliferate, researchers face a growing burden of analyzing existing work. First, not all publications relea…
- arXiv cs.AIresearchA Theoretical Framework for Understanding and Building "Any-task inference" Capable Foundation Models
arXiv:2610.40934v1 Announce Type: cross Abstract: In this work, we provide a formal framework and mathematical definition for the subset of foundation models focused on enabling the property of "any-task inference" (ATI)…
- arXiv cs.AIresearchKernel-based Interpolatory Methods for Context Compression of Attention Mechanisms
arXiv:2610.40943v1 Announce Type: cross Abstract: The bottleneck of attention mechanisms, which are the fundamental building block of modern language models, is their quadratic complexity in terms of context size. There…
- arXiv cs.AIresearchOn the Origin and Evolution of Training-Inference Mismatch in LLM Reinforcement Learning
arXiv:2610.40945v1 Announce Type: cross Abstract: On-policy reinforcement learning for large language models assumes that training responses are sampled from the current policy. In practice, an inference engine samples t…
- arXiv cs.AIresearchCAMEL: Cross-Architecture Masked Embedding Learning for Ultra-Lightweight Retinal Foundation Models
arXiv:2610.40954v1 Announce Type: cross Abstract: Recent progress in deep learning has substantially advanced automated grading of ophthalmologic pathologies, supported by large annotated datasets and improved representa…
- arXiv cs.AIresearchSteering Vectors as a Training Signal in LLM Post-Training
arXiv:2610.40998v1 Announce Type: cross Abstract: Steering vectors (SVs) are residual-stream directions that shift the behavior of LLMs when added to hidden states at inference time. While prior work has mainly used SVs…
- arXiv cs.AIresearchSTAR: Steering Action Representations during Inference
arXiv:2610.41009v1 Announce Type: cross Abstract: Vision-language-action models (VLAs) map language instructions and visual observations to robot actions, showing strong capabilities across robotic manipulation tasks. Ho…
- arXiv cs.AIresearchTowards Understanding Score-Seeking in LLMs
arXiv:2610.41014v1 Announce Type: cross Abstract: Production large language models sometimes reward-hack, exploiting flaws in how tasks are scored rather than performing the tasks as intended, sometimes in highly sophist…
- arXiv cs.AIresearchDo Language Models Know What Compelling Scientific Evidence Looks Like?
arXiv:2610.41015v1 Announce Type: cross Abstract: Expert scientists excel at weighing empirical findings from multiple sources that vary in both statistical reliability and epistemic relevance. To what extent are languag…
- arXiv cs.AIresearchDreams Are Cheaper Than Flights: Curated World-Model Data Improves Aerial Detection
arXiv:2610.41030v1 Announce Type: cross Abstract: Robot perception is increasingly data driven, yet field data is slow, costly, and sometimes disruptive to collect. Video world models offer a cheaper source: seeded with…
- arXiv cs.AIresearchWebOverlay: High-Throughput Vision-Only Distillation for Extreme Aspect-Ratio Web Overlay Detection
arXiv:2610.41037v1 Announce Type: cross Abstract: Web overlays, such as cookie consent banners, newsletter prompts, and age gates, obstruct automated web crawlers and degrade downstream document representations. While pr…
- arXiv cs.AIresearchCharacterizing Recoverable Expert-Utilization Signatures in Fine-Tuned Mixture-of-Experts LLMs
arXiv:2610.41039v1 Announce Type: cross Abstract: As Mixture-of-Experts (MoE) large language models are increasingly deployed in distributed environments, from federated learning to edge-cloud systems, their architecture…
- arXiv cs.AIagentsAccept Changes, Reject Attacks: Robust Memory Management for LLM Agents
arXiv:2610.41056v1 Announce Type: cross Abstract: Since large language model (LLM) agents rely on long-term memory, what they store now shapes what they do later. A memory manager decides how each input changes this memo…
- arXiv cs.AIresearchbf16 Rounding Silently Discards Most RL Policy Updates: A Hidden Training-Inference Mismatch and an Unbiased One-Line Fix
arXiv:2610.41073v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training of language models keeps fp32 master weights in the optimizer and serves rollouts from a bf16 copy produced by round-to-nearest…
- arXiv cs.AIresearchWhere, When, and How Many Bits? Scaling Laws for SGD with Stochastic Rounding
arXiv:2610.41074v1 Announce Type: cross Abstract: Low-precision training reduces computation but introduces additional rounding error. We theoretically study how stochastic rounding (SR) affects prediction risk as model…
- arXiv cs.AIresearchMUON-RT Reusing the Teacher's Trajectory for Momentum-Free Muon for LLM Self-Distillation
arXiv:2610.41104v1 Announce Type: cross Abstract: Self-distillation methods for large language models with an exponential moving average (EMA) teacher already retain a history of student updates. Muon nevertheless stores…
- arXiv cs.AIresearchOne Verdict Is Not Enough: Regression Testing Learned World Models and Their Test Harnesses
arXiv:2610.41130v1 Announce Type: cross Abstract: Learned world models ship as software components whose model versions, preprocessing, and test harnesses change between releases. Work on model updates already counts per…
- arXiv cs.AIagentsWhen Disclosure Is Compulsory: Evaluating Ride-Hailing Rebalancing Policies with Self-Interested LLM Driver Agents
arXiv:2610.41132v1 Announce Type: cross Abstract: The EU Platform Work Directive, to be transposed by December 2026, requires ride-hailing platforms to state in plain language the main parameters of their automated decis…
- arXiv cs.AIresearchLineage Is Memory: Parent Inheritance and Feedback Disclosure in Short-Budget LLM-Guided Optimization
arXiv:2610.41157v1 Announce Type: cross Abstract: Iterative language-model optimizers refine prompts and programs by evaluating a candidate, showing a proposer model a sample of failing cases, and keeping revisions that…
- arXiv cs.AIresearchARK: Avoiding Routing Collisions for KV Cache Transfer in Disaggregated LLM Inference
arXiv:2610.41160v1 Announce Type: cross Abstract: Disaggregated LLM inference separates the prefill and decode phases across GPU pools, generating massive KV-cache transfers. Because these transfers last hundreds of mill…
- arXiv cs.AIresearchROSTrans: Empirically Benchmarking LLMs for ROS1-to-ROS2 Migration
arXiv:2610.41168v1 Announce Type: cross Abstract: Although large language models have shown strong capabilities in domain-specific code generation, their performance in robotics software development, especially for the R…
- arXiv cs.AIagentsContext as Infrastructure: Knowledge Compilation for Retrieval in Agentic Systems with Harnesses
arXiv:2610.41172v1 Announce Type: cross Abstract: Retrieval-augmented generation is becoming agentic. A search harness writes queries, reads results, reformulates, and decides when to stop. This largely solves accuracy:…
- arXiv cs.AIresearchBeyond CLIP: Calibrated (Few-Shot) Defect Detection With System One Decision Models
arXiv:2610.41199v1 Announce Type: cross Abstract: Cameras and vision sensors are widely used for product and process inspection in manufacturing environments. Traditionally, this process required thousands of images of b…
- arXiv cs.AIresearchFrom Evaluation to Evolution: Benchmarking Image Editing and Evolving Image Models
arXiv:2610.41210v1 Announce Type: cross Abstract: Real-world image editing requires coordinating multiple visual transformations with content preservation and reference constraints, yet aggregate scores can readily obscu…
- arXiv cs.AIresearchCoarse3D: Controllable and Faithful Sparse Structure Generation for Image-to-3D
arXiv:2610.41231v1 Announce Type: cross Abstract: Coarse-to-fine 3D-native generation relies heavily on the first-stage sparse structure, which determines the global orientation and overall geometry for subsequent refine…
- arXiv cs.AIagentsANGLER: Verifier-Grounded Benchmarking with an Adaptive Attacker for Web Agents
arXiv:2610.41272v1 Announce Type: cross Abstract: Web agents are increasingly deployed to complete tasks autonomously on real websites, where adversarially injected content can induce them to perform unauthorized actions…
- arXiv cs.AIagentsIn-Model Context Compression with Agentic Soft Tokens for Long-Horizon LLM Agents
arXiv:2610.41291v1 Announce Type: cross Abstract: Long-horizon LLM agents play an important role in solving complex and sustained tasks, with ever-growing interaction contexts. However, these accumulated contexts will ra…
- arXiv cs.AIagentsART of PIV: Agentic Real-Time Particle Image Velocimetry for Active Flow Control
arXiv:2610.41304v1 Announce Type: cross Abstract: Particle image velocimetry (PIV) measures fluid motion from images of tracer particles, but its accuracy depends on choices throughout the estimation pipeline, including…
- arXiv cs.AIresearchErase the Injected Region: Multimodal Prompt-Injection Defense with On-Policy Self-Distillation
arXiv:2610.41307v1 Announce Type: cross Abstract: Multimodal indirect prompt injection embeds malicious instructions in external media that also contains information needed for the user's task. Existing defenses can bloc…
- arXiv cs.AIresearchGenDSR: Transferring Representations from Video Generation Models for Dynamic Spatial Reasoning
arXiv:2610.41314v1 Announce Type: cross Abstract: Dynamic spatial reasoning is essential for connecting visual intelligence to thephysical world, yet remains challenging for vision-language models (VLMs), which must pres…
- arXiv cs.AIresearchTransferring Peptide-Target Interaction Patterns to Small Molecules by Joint Guidance for Diffusion and Flow Matching
arXiv:2610.41322v1 Announce Type: cross Abstract: Generating small molecules to target protein-protein interactions (PPIs) remains one of the most challenging yet high-reward frontiers in drug discovery. Unlike tradition…
- arXiv cs.AIresearchWith foundation-model features, aggregator complexity does not improve cross-hospital discrimination in gastric whole-slide image classification
arXiv:2610.41328v1 Announce Type: cross Abstract: Whole-slide image classifiers are usually developed within one hospital and often go untested at unseen hospitals. We assembled 5,036 haematoxylin-and-eosin-stained gastr…
- arXiv cs.AIresearchPinching Antennas for ISAC: Waveguide Architectures, Solutions, and Future Directions
arXiv:2610.41380v1 Announce Type: cross Abstract: Integrated sensing and communication (ISAC) is a core design principle for sixth-generation (6G) wireless systems, yet fixed antenna geometry limits its performance. Pinc…
- arXiv cs.AIresearchFrom prediction error to sparse events: Biologically inspired signed-dyadic coding for Mandarin keyword spotting
arXiv:2610.41381v1 Announce Type: cross Abstract: In continuous spiking keyword spotting, temporally correlated acoustic frames can repeatedly trigger memory access and neural computation at a dense input interface, even…
- arXiv cs.AIresearchProSearch: Benchmarking Multi-Constraint Protocol Retrieval in Experimental Science
arXiv:2610.41396v1 Announce Type: cross Abstract: In AI for Science scenarios, experimental design and method reproduction require retrieving protocols that satisfy multiple interdependent constraints, yet existing bench…
- arXiv cs.AIresearchDistilling Knowledge from Search: Decoder Model Factory for Quantum LDPC Codes
arXiv:2610.41398v1 Announce Type: cross Abstract: We introduce GraphMP, a learning-based message-passing decoder for quantum low-density parity-check codes that transfers without fine-tuning across code families, code si…
- arXiv cs.AIagentsWhen Safety Checks Become Privacy Risks: A Privacy-Preserving Paradigm for LLM Agent Safety Auditing
arXiv:2610.41401v1 Announce Type: cross Abstract: Large language model agents interact with online services through tool calls that may access private data or perform sensitive actions. Specialized providers can supply a…
- arXiv cs.AIresearchSparseGDN: Chunk Sparse in Linear Attention
arXiv:2610.41420v1 Announce Type: cross Abstract: Gated Delta Networks (GDNs) offer linear-time sequence modeling, yet long-context prefill remains costly due to dense intra-chunk computation, recurrent-state updates, an…
- arXiv cs.AIagentsBlindToChange: AI Agents Can Find Changes When Asked But Do They Look When Needed?
arXiv:2610.41435v1 Announce Type: cross Abstract: Given that AI agents can search the web broadly and deeply in real time, it is tempting to conclude that their outputs account for recent world events. We show that this…
- arXiv cs.AIresearchFrom Representation to Readout: Mechanistic Analysis of Membership Signals in Language Models
arXiv:2610.41445v1 Announce Type: cross Abstract: Membership inference aims to determine whether a particular example was included in a model's training data. Such membership signals are often broadly described as memori…
- arXiv cs.AIagentsKEEPER: Learning Control-Sufficient Textual Memory for Long-Horizon LLM Agents
arXiv:2610.41482v1 Announce Type: cross Abstract: Recursive textual memory can carry earlier errors into later updates, yet task performance alone does not establish memory reliability. We define self-consistency bias as…
- arXiv cs.AIresearchSparse Text Diffusion under Dual Budgets: Context Connectivity and Expert Activation
arXiv:2610.41487v1 Announce Type: cross Abstract: Long-context diffusion repeatedly pays for both token interaction and feed-forward computation. We formulate these costs as two separate budgets: the edges available to a…
- arXiv cs.AIresearchORION: An Outcome-Driven LLM Advisor for RL-Based Multi-Domain 6G Slice Placement
arXiv:2610.41563v1 Announce Type: cross Abstract: Deploying 6G network slices across administrative domains requires an online decision for each arriving request: which domain hosts each virtual network function, how tra…